Notes

3 dimensional visual two-mirror code reader along with focus-tunable lens.
Digital technologies provide a platform for accelerating science and broadening impact in behavioral medicine.

The objective of this invited keynote presentation or paper is to offer a blueprint for navigating the rapidly changing waters of digital health.

A strategic literature review on digital health technologies in behavioral medicine was combined with a review of relevant policy initiatives to yield insights on (a) knowledge building, (b) collaboration, and (c) public health stewardship.

Digital platforms offer unprecedented leverage for accelerating science, facilitating collaboration, and advancing public health. Early successes in behavioral medicine demonstrated how digital platforms could extend the reach of theory-based behavioral therapeutics through increases in efficiency and scale. As medical investments in health information technology increased, the field of behavioral informatics emerged as the collaborative glue binding behavioral theory into a new generation of patient-facing appli.Over the past 20 years, tobacco prevention and cessation efforts have evolved to keep pace with the changing tobacco product landscape and the widespread adoption of digital technologies. In 2019, Truth Initiative was awarded the Society of Behavioral Medicine's Jessie Gruman Award for Health Engagement in recognition of the major role it has played on both fronts since its inception in 1999. This manuscript reviews the challenges and opportunities that have emerged over the past two decades, the evolving tactics deployed by Truth Initiative to engage people in tobacco prevention and cessation efforts, the approaches used to evaluate those efforts, and key achievements. It concludes with a summary of lessons learned and considerations for tobacco control researchers and practitioners to accelerate their impact on public health.
Artificial Intelligence (AI) is transforming the process of scientific research. AI, coupled with availability of large datasets and increasing computational power, is accelerating progress in areas such as genetics, climate change and astronomy [NeurIPS 2019 Workshop Tackling Climate Change with Machine Learning, Vancouver, Canada; Hausen R, Robertson BE. Morpheus A deep learning framework for the pixel-level analysis of astronomical image data. Astrophys J Suppl Ser. 2020;24820; Dias R, Torkamani A. AI in clinical and genomic diagnostics. Genome Med. 2019;1170.]. The application of AI in behavioral science is still in its infancy and realizing the promise of AI requires adapting current practices.

By using AI to synthesize and interpret behavior change intervention evaluation report findings at a scale beyond human capability, the HBCP seeks to improve the efficiency and effectiveness of research activities. We explore challenges facing AI adoption in behavioral science through the lens of lessons learnns from incomplete data.

AI holds promise for achieving the goal of predicting outcomes of behavior change interventions, based on information that is automatically extracted from intervention evaluation reports. This information can be used to train knowledge systems using machine learning and reasoning algorithms.
AI holds promise for achieving the goal of predicting outcomes of behavior change interventions, based on information that is automatically extracted from intervention evaluation reports. This information can be used to train knowledge systems using machine learning and reasoning algorithms.Land plants evolved from a single group of streptophyte algae. One of the key factors needed for adaptation to a land environment is the modification of the peripheral antenna systems of photosystems. Here, the photosystems of Mesostigma viride, an earliest-branched streptophyte alga, were analyzed to gain insight into their evolution. Iso-seq and phylogenetic analyses of Light-Harvesting Complexes (LHCs) revealed that M. viride possesses three algae-specific LHCs, including algae-type LHCA2, LHCA9, and LHCP; while the streptophyte-specific LHCB6 was not identified. These data suggest that the acquisition of LHCB6 and the loss of algae-type LHCs occurred after the M. viride lineage branched off from other streptophytes. Clear-native (CN)-PAGE resolved the photosynthetic complexes, including the PSI-PSII megacomplex, PSII-LHCII, two PSI-LHCI-LHCIIs, PSI-LHCI, and the LHCII trimer. Results indicated that the higher-molecular weight PSI-LHCI-LHCII likely had more LHCII than the lower-molecular weight one, a unique feature of M. viride photosystems. CN-PAGE coupled with mass spectrometry strongly suggested that the LHCP was bound to PSII-LHCII, while the algae-type LHCA2 and LHCA9 were bound to PSI-LHCI, both of which are different from those in land plants. Results of the present study strongly suggest that M. viride photosystems possess unique features that were inherited from a common ancestor of streptophyte and chlorophyte algae.Contraction of skeletal muscle is regulated by structural changes in both actin-containing thin filaments and myosin-containing thick filaments, but myosin-based regulation is unlikely to be preserved after thick filament isolation, and its structural basis remains poorly characterized. Here, we describe the periodic features of the thick filament structure in situ by high-resolution small-angle x-ray diffraction and interference. We used both relaxed demembranated fibers and resting intact muscle preparations to assess whether thick filament regulation is preserved in demembranated fibers, which have been widely used for previous studies. We show that the thick filaments in both preparations exhibit two closely spaced axial periodicities, 43.1 nm and 45.5 nm, at near-physiological temperature. The shorter periodicity matches that of the myosin helix, and x-ray interference between the two arrays of myosin in the bipolar filament shows that all zones of the filament follow this periodicity. The 45.5-nm repeatitions used for most previous studies with this preparation.Here we report on the existence and functionality of the immune checkpoint signal regulatory protein α (SIRPα) in NK cells and describe how it can be modulated for cell therapy. NK cell SIRPα is up-regulated upon IL-2 stimulation, interacts with target cell CD47 in a threshold-dependent manner, and counters other stimulatory signals, including IL-2, CD16, or NKG2D. Elevated expression of CD47 protected K562 tumor cells and mouse and human MHC class I-deficient target cells against SIRPα+ primary NK cells, but not against SIRPα- NKL or NK92 cells. SIRPα deficiency or antibody blockade increased the killing capacity of NK cells. Selleckchem PX-12 Overexpression of rhesus monkey CD47 in human MHC-deficient cells prevented cytotoxicity by rhesus NK cells in a xenogeneic setting. The SIRPα-CD47 axis was found to be highly species specific. Together, the results demonstrate that disruption of the SIRPα-CD47 immune checkpoint may augment NK cell antitumor responses and that elevated expression of CD47 may prevent NK cell-mediated killing of allogeneic and xenogeneic tissues.
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